The prospect of employing chemoimmunotherapy targeted towards the endoplasmic reticulum (ER) presents an opportunity to amplify the synergistic effects of chemotherapy and immunotherapy. In this study, we initially validated celastrol (CEL) as an inducer of immunogenic cell death (ICD) by promoting ER stress and autophagy in colorectal cancer (CRC) cells. Subsequently, an ER-targeted strategy was posited, involving the codelivery of CEL with PD-L1 small interfering RNAs (siRNA) using KDEL peptide-modified exosomes derived from milk (KME), to enhance chemoimmunotherapy outcomes. Our findings demonstrate the efficient transportation of KME to the ER via the Golgi-to-ER pathway. Compared to their non-targeting counterparts, KME exhibited a significant augmentation of the CEL-induced ICD effect. Additionally, it facilitated the release of danger signaling molecules (DAMPs), thereby stimulating the antigen-presenting function of dendritic cells and promoting the infiltration of T cells into the tumor. Concurrently, the ER-targeted delivery of PD-L1 siRNA resulted in the downregulation of both intracellular and membrane PD-L1 protein expression, consequently fostering the proliferation and activity of CD8+ T cells. Ultimately, the ER-targeted formulation exhibited enhanced anti-tumor efficacy and provoked anti-tumor immune responses against orthotopic colorectal tumors in vivo. Collectively, a robust ER-targeted delivery strategy provides an encouraging approach for achieving potent cancer chemoimmunotherapy.

A patient with a PD-L1-negative, TMB-low, KEAP1/STK11 co-mutated metastatic non-small cell lung cancer (NSCLC) experienced a multisite radiological progression at 3 months after initiation of chemoimmunotherapy as first-line treatment for metastatic disease. After the radiological progression, while she was not undergoing treatment, the patient had spontaneous lesions shrinkage and further achieved a prolonged complete response. Genomic and transcriptomic data collected at baseline and at the time of pseudoprogression allowed us to biologically characterize this rare response pattern. We observed the presence of a tumor-specific T-cell response against tumor-specific neoantigens (TNAs). Endogenous retroviruses (ERVs) expression following chemoimmunotherapy was also observed, concurrent with biological features of an anti-viral-like innate immune response with type I IFN signaling and production of CXCR3-associated chemokines. This is the first biological characterization of a NSCLC pseudoprogression under chemoimmunotherapy followed by a prolonged complete response in a PD-L1-negative, TMB-low, KEAP1/STK11 co-mutated NSCLC. These clinical and biological data underline that even patients with multiple factors of resistance to immune checkpoint inhibitors could trigger a tumor-specific immune response to tumor neoantigen, leading to complete eradication of the tumor and probably a vaccinal immune response.

BACKGROUND: The impact of chemoimmunotherapy (CIT) on immunoglobulin (Ig) quantities in patients with chronic lymphocytic leukemia (CLL) has not been extensively studied.
METHODS: We analyzed Ig levels in 45 stable patients with indolent CLL (without indication for treatment) and 87 patients with progressive disease before first-line treatment. Fifty-five patients were evaluated again after the treatment with CIT.
RESULTS: We observed significantly lower levels of all Ig classes and subclasses in patients with progressive disease compared to patients with indolent disease. After treatment, median IgA increased from 0.59 g/L to 0.74 g/L (p = 0.0031). In stable patients, lower IgA2 was associated with shorter time to first treatment, although it did not reach statistical significance (p = 0.056). Shorter overall survival was observed in patients with progressive disease and lower IgG2 (p = 0.043). Surprisingly, among the patients with progressive CLL, unmutated IGHV genes were associated with higher levels of IgG, IgG1 and IgM, while TP53 mutation and/or 17p deletion were associated with higher levels of IgA and IgA1.
CONCLUSIONS: CIT may lead to increase in IgA levels. Hypogammaglobulinemia is more common in patients with progressive CLL and unmutated IGHV or TP53 dysfunction.

Pseudoprogression of malignancy in patients treated with systemic immunotherapy is a well- recognised phenomenon and has also been seen in patients treated with combined chemoimmunotherapy. Neoadjuvant chemoimmunotherapy prior to surgery is a relatively new treatment strategy for the management of many malignancies. We report the case of a patient who was suspected to have primary lung squamous cell carcinoma progression following neoadjuvant chemoimmunotherapy. Tissue histopathology from biopsies demonstrated granulomatous sarcoid-like inflammation rather than progression or metastatic disease. The patient proceeded to have successful surgical clearance of residual tumour. Significantly, failure to suspect granulomatous reactions and pseudoprogression has profound influence on the trajectory of patient care, such as, the potential for patients to miss out on curative surgery. In this case report and review of the literature, we evaluate the role of pseudoprogression and the need for radiologists to be aware of this phenomenon so that they do not mistakenly report new metastases and derail the treatment paradigm for patients with curable malignant conditions.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the primary form of lung cancer, and the combination of chemotherapy with immunotherapy offers promising treatment options for patients suffering from this disease. However, the emergence of drug resistance significantly limits the effectiveness of these therapeutic strategies. Consequently, it is imperative to devise methods for accurately detecting and evaluating the efficacy of these treatments.
OBJECTIVE: To identify the metabolic signatures associated with neutrophil extracellular traps (NETs) and chemoimmunotherapy efficacy in NSCLC patients.
METHODS: In total, 159 NSCLC patients undergoing first-line chemoimmunotherapy were enrolled. We first investigated the characteristics influencing clinical efficacy. Circulating levels of NETs and cytokines were measured by commercial kits. Liquid chromatography tandem mass spectrometry quantified plasma metabolites, and differential metabolites were identified. Least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and random forest algorithms were employed. By using plasma metabolic profiles and machine learning algorithms, predictive metabolic signatures were established.
RESULTS: First, the levels of circulating interleukin-8, neutrophil-to-lymphocyte ratio, and NETs were closely related to poor efficacy of first-line chemoimmunotherapy. Patients were classed into a low NET group or a high NET group. A total of 54 differential plasma metabolites were identified. These metabolites were primarily involved in arachidonic acid and purine metabolism. Three key metabolites were identified as crucial variables, including 8,9-epoxyeicosatrienoic acid, L-malate, and bis(monoacylglycerol)phosphate (18:1/16:0). Using metabolomic sequencing data and machine learning methods, key metabolic signatures were screened to predict NET level as well as chemoimmunotherapy efficacy.
CONCLUSIONS: The identified metabolic signatures may effectively distinguish NET levels and predict clinical benefit from chemoimmunotherapy in NSCLC patients.

UNASSIGNED: This study aimed to establish a comprehensive clinical prognostic risk model based on pulmonary function tests. This model was intended to guide the evaluation and predictive management of patients with resectable stage I-III non-small cell lung cancer (NSCLC) receiving neoadjuvant chemoimmunotherapy.
UNASSIGNED: Clinical pathological characteristics and prognostic survival data for 175 patients were collected. Univariate and multivariate Cox regression analyses, and least absolute shrinkage and selection operator (LASSO) regression analysis were employed to identify variables and construct corresponding models. These variables were integrated to develop a ridge regression model. The models\' discrimination and calibration were evaluated, and the optimal model was chosen following internal validation. Comparative analyses between the risk scores or groups of the optimal model and clinical factors were conducted to explore the potential clinical application value.
UNASSIGNED: Univariate regression analysis identified smoking, complete pathologic response (CPR), and major pathologic response (MPR) as protective factors. Conversely, T staging, D-dimer/white blood cell ratio (DWBCR), D-dimer/fibrinogen ratio (DFR), and D-dimer/minute ventilation volume actual ratio (DMVAR) emerged as risk factors. Evaluation of the models confirmed their capability to accurately predict patient prognosis, exhibiting ideal discrimination and calibration, with the ridge regression model being optimal. Survival analysis demonstrated that the disease-free survival (DFS) in the high-risk group (HRG) was significantly shorter than in the low-risk group (LRG) (P=2.57×10-13). The time-dependent receiver operating characteristic (ROC) curve indicated that the area under the curve (AUC) values at 1 year, 2 years, and 3 years were 0.74, 0.81, and 0.79, respectively. Clinical correlation analysis revealed that men with lung squamous cell carcinoma or comorbid chronic obstructive pulmonary disease (COPD) were predominantly in the LRG, suggesting a better prognosis and potentially identifying a beneficiary population for this treatment combination.
UNASSIGNED: The prognostic model developed in this study effectively predicts the prognosis of patients with NSCLC receiving neoadjuvant chemoimmunotherapy. It offers valuable predictive insights for clinicians, aiding in developing treatment plans and monitoring disease progression.

The clinical application and biological function of interferon regulatory factor 1 (IRF1) in non-small cell lung cancer (NSCLC) patients undergoing chemoimmunotherapy remain elusive. The aim of this study was to investigate the predictive and prognostic significance of IRF1 in NSCLC patients. We employed the cBioPortal database to predict frequency changes in IRF1 and explore its target genes. Bioinformatic methods were utilized to analyze the relationship between IRF1 and immune regulatory factors. Retrospective analysis of clinical samples was conducted to assess the predictive and prognostic value of IRF1 in chemoimmunotherapy. Additionally, A549 cells with varying IRF1 expression levels were constructed to investigate its effects on NSCLC cells, while animal experiments were performed to study the role of IRF1 in vivo. Our findings revealed that the primary mutation of IRF1 is deep deletion and it exhibits a close association with immune regulatory factors. KRAS and TP53 are among the target genes of IRF1, with interferon and IL-2 being the predominantly affected pathways. Clinically, IRF1 levels significantly correlate with the efficacy of chemoimmunotherapy. Patients with high IRF1 levels exhibited a median progression-free survival (mPFS) of 9.5 months, whereas those with low IRF1 levels had a shorter mPFS of 5.8 months. IRF1 levels positively correlate with PD-L1 distribution and circulating IL-2 levels. IL-2 enhances the biological function of IRF1 and recapitulates its role in vivo in the knockdown group. Therefore, IRF1 may possess predictive and prognostic value for chemoimmunotherapy in NSCLC patients through the regulation of the IL-2 inflammatory pathway.

Patients with advanced NSCLC have heterogenous responses to immune checkpoint inhibitors (ICIs) with or without chemotherapy. In NSCLC, the impact of the distribution of metastatic sites and the response to systemic therapy combinations remain poorly understood. In a retrospective cohort study of patients with unresectable stage III/IV NSCLC who received first-line systemic therapy, we sought to assess the association between the site of metastases with patterns of response and progression. Data regarding demographics, tumour characteristics (including site, size, and volume of metastases), treatment, and outcomes were examined at two cancer care centres. The endpoints included organ site-specific response rate, objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). Two-hundred and eighty-five patients were included in the analysis. In a multivariate analysis, patients with bone metastases had a reduced ORR, PFS, and OS. Primary resistance was also more likely in patients with bone metastases. Patients with bone or liver metastases had a shorter OS when receiving ICIs with or without chemotherapy, but not with chemotherapy alone, suggesting an immunological basis for therapeutic resistance. A directed assessment of the tumour microenvironment in these locations and a deeper understanding of the drivers of organ-specific resistance to immunotherapy are critical to optimise novel combination therapies and sequencing in these patients.

BACKGROUND: There is an urgent need to find a reliable and effective imaging method to evaluate the therapeutic efficacy of immunochemotherapy in advanced non-small cell lung cancer (NSCLC). This study aimed to investigate the capability of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) histogram analysis based on different region of interest (ROI) selection methods for predicting treatment response to chemoimmunotherapy in advanced NSCLC.
METHODS: Seventy-two stage III or IV NSCLC patients who received chemoimmunotherapy were enrolled in this study. IVIM and DKI were performed before treatment. The patients were classified as responders group and non-responders group according to the Response Evaluation Criteria in Solid Tumors 1.1. The histogram parameters of ADC, Dslow, Dfast, f, Dk and K were measured using whole tumor volume ROI and single slice ROI analysis methods. Variables with statistical differences would be included in stepwise logistic regression analysis to determine independent parameters, by which the combined model was also established. And the receiver operating characteristic curve (ROC) were used to evaluate the prediction performance of histogram parameters and the combined model.
RESULTS: ADC, Dslow, Dk histogram metrics were significantly lower in the responders group than in the non-responders group, while the histogram parameters of f were significantly higher in the responders group than in the non-responders group (all P < 0.05). The mean value of each parameter was better than or equivalent to other histogram metrics, where the mean value of f obtained from whole tumor and single slice both had the highest AUC (AUC = 0.886 and 0.812, respectively) compared to other single parameters. The combined model improved the diagnostic efficiency with an AUC of 0.968 (whole tumor) and 0.893 (single slice), respectively.
CONCLUSIONS: Whole tumor volume ROI demonstrated better diagnostic ability than single slice ROI analysis, which indicated whole tumor histogram analysis of IVIM and DKI hold greater potential than single slice ROI analysis to be a promising tool of predicting therapeutic response to chemoimmunotherapy in advanced NSCLC at initial state.

Myeloid-derived suppressor cells (MDSCs) have played a significant role in facilitating tumor immune escape and inducing an immunosuppressive tumor microenvironment. Eliminating MDSCs and tumor cells remains a major challenge in cancer immunotherapy. A novel approach has been developed using gemcitabine-celecoxib twin drug-based nano-assembled carrier-free nanoparticles (GEM-CXB NPs) for dual depletion of MDSCs and tumor cells in breast cancer chemoimmunotherapy. The GEM-CXB NPs exhibit prolonged blood circulation, leading to the preferential accumulation and co-release of GEM and CXB in tumors. This promotes synergistic chemotherapeutic activity by the proliferation inhibition and apoptosis induction against 4T1 tumor cells. In addition, it enhances tumor immunogenicity by immunogenic cell death induction and MDSC-induced immunosuppression alleviation through the depletion of MDSCs. These mechanisms synergistically activate the antitumor immune function of cytotoxic T cells and natural killer cells, inhibit the proliferation of regulatory T cells, and promote the M2 to M1 phenotype repolarization of tumor-associated macrophages, considerably enhancing the overall antitumor and anti-metastasis efficacy in BALB/c mice bearing 4T1 tumors. The simplified engineering of GEM-CXB NPs, with their dual depletion strategy targeting immunosuppressive cells and tumor cells, represents an advanced concept in cancer chemoimmunotherapy.